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arXiv · 2609.05601

A compact time-frequency representation for gravitational-wave data analysis

Noah Pearson·Mesut Çalışkan·Sophie Bini·Neil J. Cornish
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Abstract

Time-frequency (wavelet) domain analyses are seeing greater use for gravitational-wave data analysis due to the advantages they have in handling non-stationary noise. A popular choice is the Wilson-Daubechies-Meyer (WDM) wavelet transform, which uses a window function that is very compact in frequency, but more spread out in time. In this work, we consider an alternative window function that is built from a sum of phase-shifted Gaussians. This "Gaussian" window is more symmetric in time-frequency, and consequently more compact. We examine the properties of this window function and the implications it has for gravitational-wave analyses. We calculate the window's time-frequency variance product analytically and verify it numerically. For the symmetric case, where the window has the same form in time and frequency, the construction comes within $\sim2.4\%$ of saturating the Heisenberg-Gabor uncertainty limit. We conjecture that this Gaussian window achieves the minimum time-frequency area of any WD wavelet window.

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Noah Pearson, Mesut Çalışkan, Sophie Bini, Neil J. Cornish. 2026-09-04. A compact time-frequency representation for gravitational-wave data analysis. https://arxiv.org/abs/2609.05601

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